Update app.py

app.py

@@ -3,9 +3,22 @@ import os
 from datasets import load_dataset
 import pandas as pd
 import matplotlib.pyplot as plt
+import argilla as rg
 
+
+ARGILLA_API_URL = os.environ.get("ARGILLA_API_URL")
+ARGILLA_API_KEY = os.environ.get("ARGILLA_API_KEY")
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
+client =  rg.Argilla(
+    api_url=ARGILLA_API_URL,
+    api_key=ARGILLA_API_KEY
+)
+
+workspace = client.workspaces('cohere')
+
+users_map = {str(user.id):user.username for user in list(workspace.users)}
+
 ds = load_dataset("CohereForAI/mmlu-translations-results", split="train", token=HF_TOKEN)
 
 df = ds.to_pandas()
@@ -40,14 +53,14 @@ st.pyplot(fig)
 user_ids = df['responses'].apply(lambda x: x['is_edit_required']).explode().apply(lambda x: x['user_id'])
 user_id_counts = user_ids.value_counts()
 
+# Map user IDs to usernames
+user_id_counts.index = user_id_counts.index.map(users_map)
+
 # Convert the user ID counts to a DataFrame for display in the table
 user_id_counts_df = user_id_counts.reset_index()
-user_id_counts_df.columns = ['User ID', 'Count']
+user_id_counts_df.columns = ['Username', 'Count']
 
-# Display the table of user ID counts in the Streamlit app
+# Display the table of username counts in the Streamlit app
 st.table(user_id_counts_df)
 
-st.dataframe(df)
-
-
-
+st.dataframe(df)